Abstract: A method and system are disclosed for identifying a trailer or trailer coupler in an image. The method includes obtaining a database of descriptor clusters. Each descriptor cluster has at least one label assigned thereto. Each at least one label is a label for a trailer or trailer coupler, or for a background. Image data pertaining to an image is received. Features and descriptors are determined in the received image data. For each determined descriptor, the method includes matching the determined descriptor with a descriptor cluster in the database and assigning the label corresponding to the matched descriptor cluster to the determined descriptor. Based upon the determined descriptors having the assigned label corresponding to one of a trailer or a trailer coupler, the method includes determining a convex hull of a representation of the one of the trailer or trailer coupler in the image.

Abstract: A method for determining a location of a trailer in an image includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch describing at least one real-time image. A convolution is performed of the feature patch and each filter from a set of filters with the filter being based on data representative of known trailers. A location of a trailer is determined in the at least one real-time image based on the convolution between the feature patch and each filter from the set of filters.

Abstract: A localization and mapping system and method for a motor vehicle is disclosed and includes at least one camera configured to obtain images of an environment surrounding the motor vehicle, at least one sensor configured to obtain location information for objects surrounding the motor vehicle and a controller configured to receive the images captured by the at least one camera and the location information obtained by the at least one sensor. The controller enhances the captured images utilizing a neural network and combines the enhanced images with the location information to localize the vehicle within the mapped environment.

Abstract: An automated parking system for a vehicle includes a camera configured to obtain images of objects proximate the vehicle, and a controller configured to review the obtained images of objects proximate the vehicle to classify an environment proximate the vehicle, determine a type of parking lot associated with the classified location and initiate an automated parking function of the vehicle corresponding to the determined type of parking lot.

Abstract: An automated vehicle parking system for a motor vehicle is disclosed and includes at least one camera obtaining images proximate a vehicle, at least one sensor array detecting objects proximate the vehicle, and a controller configured to generate a mask of an area proximate the vehicle from the images obtained by the at least one camera including labeled features identified within the obtained images and project the generated mask onto an occupancy grid generated with information from the at least one sensor array, wherein the controller is configured to locate a parking space responsive to open spaces defined within the generated mask.

Abstract: A method for determining a trailer angle between a tow vehicle and a trailer attached to the tow vehicle includes receiving images from a camera positioned on a rear portion of the tow vehicle with a data processing hardware device, determining visual features from the images, tracking the visual features while the tow vehicle and trailer are moving and calculating, at the data processing hardware, the trailer angle based on the visual features. The trailer angle is then transmitted from the data processing hardware to one or more vehicle systems.

Abstract: A method for visual trailer tracking of vehicle-trailer angle estimation, including: (a) camera receiving images, each most recently received image being identified as a current image, replacing a previously identified current image; (b) during a driving maneuver, extracting visual features from the current image, calculating a trailer angle from the current image, and storing the current image as a reference image, the trailer angle as a trailer angle reference and the extracted visual features as visual reference features; and (c) matching the visual features from the current image with the visual reference features. When a number of matches is below a threshold, repeating operation (c) to update the reference image, the trailer angle reference and the visual reference features. The method includes calculating a trailer angle between a trailer representation in the current image and a trailer representation in the reference image based in part upon the trailer angle reference.

Abstract: A vehicle driver assist system provides for the location of a target feature in an initial image and updates the location of that target feature based on information indicative of vehicle dynamic operation. The system predicts a relative position of the target feature within subsequent images such that only a portion of subsequent images need by analyzed and searched.

Abstract: A method and system for a vehicle control system generates maps utilized for charting a path of a vehicle through an environment. The method performed by the system obtains information indicative of vehicle movement from at least one vehicle system and images including objects within an environment from a camera mounted on the vehicle. The system uses the gathered information and images to create a depth map of the environment. The system also generates an image point cloud map from images taken with a vehicle camera and a radar point cloud map with velocity information from a radar sensor mounted on the vehicle. The depth map and the point cloud maps are fused together and any dynamic objects filtered out from the final map used for operation of the vehicle.

Abstract: A method and system for creating a map of an environment surrounding a vehicle includes a camera for obtaining images including objects within an environment from at least one camera mounted on the vehicle and a controller configured to create a depth map of the environment based on the images and vehicle odometry information. A laser scan of the depth map is created and used to create a two-dimensional map utilized for operating the vehicle.

Abstract: A method and system for locating and tracking a trailer coupler for autonomous vehicle operation is disclosed. The system converts an image from a vehicle camera to a depth map that includes a plurality of points indicative of a distance between an object within the image and a reference point. The system used the depth map to identify and track a coupler of a trailer.

Abstract: A method for determining a position of a tow ball in an image. The method includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch (f) describing at least one real-time image. A convolution is performed of the feature patch (f) and each filter (h) from a set of filters (H) with the filter (h) being based on data representative of known tow hitches fixed to the vehicle. A location of a tow ball on the tow hitch is identified in the at least one real-time image is based on the convolution between the feature patch (f) and each filter (h) from the set of filters (H).

Abstract: A method for determining a location of a trailer in an image includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch describing at least one real-time image. A convolution is performed of the feature patch and each filter from a set of filters with the filter being based on data representative of known trailers. A location of a trailer is determined in the at least one real-time image based on the convolution between the feature patch and each filter from the set of filters.

Abstract: A localization and mapping system and method for a motor vehicle is disclosed and includes at least one camera configured to obtain images of an environment surrounding the motor vehicle, at least one sensor configured to obtain location information for objects surrounding the motor vehicle and a controller configured to receive the images captured by the at least one camera and the location information obtained by the at least one sensor. The controller enhances the captured images utilizing a neural network and combines the enhanced images with the location information to localize the vehicle within the mapped environment.

Abstract: A method for autonomously maneuvering a tow vehicle towards a trailer positioned behind the tow vehicle is provided. The method includes receiving one or more images from one or more cameras positioned on a back portion of the tow vehicle. The method also includes identifying a trailer representation within the one or more images. The trailer representation being indicative of the trailer positioned behind the tow vehicle. The method also includes setting a vertical center of the trailer representation as a target. The method also includes determining a first steering wheel angle to turn the tow vehicle such that the vehicle autonomously maneuvers in a direction towards the target. The method also includes transmitting instructions to a drive system causing the tow vehicle to maneuver based on the first steering wheel angle.

Abstract: A method for calibrating extrinsic parameters (182) of a trailer camera (132d, 132e, 132f) supported by a trailer (106) attached to a tow vehicle (102). The method includes determining a three-dimensional feature map (162) from one or more vehicle images (133) received from a camera (132a, 132b, 132c) supported by the tow vehicle and identifying reference points (163) within the three-dimensional feature map. The method includes detecting the reference points within one or more trailer images received from the trailer camera after the vehicle and the trailer moved a predefined distance in the forward direction. The method also includes determining a trailer camera location (172) of the trailer camera (132d, 132e, 132f) relative to the three-dimensional feature map (162) and determining a trailer reference point (184) based on the trailer camera location. The method also includes determining extrinsic parameters (182) of the trailer camera relative to the trailer reference point.

Abstract: An automated parking system for a vehicle according to an exemplary embodiment of this disclosure includes, among other possible things, a camera configured to obtain images of objects proximate the vehicle, and a controller configured to review the obtained images of objects proximate the vehicle to classify a location of the vehicle, determine a height of overhead objects associated with the classified location and initiate an automated parking function of the vehicle that corresponds to the determined height of the overhead objects.

Abstract: An automated parking system for a vehicle includes a camera configured to obtain images of objects proximate the vehicle, and a controller configured to review the obtained images of objects proximate the vehicle to classify an environment proximate the vehicle, determine a type of parking lot associated with the classified location and initiate an automated parking function of the vehicle corresponding to the determined type of parking lot.

Abstract: A method of visual-inertial odometry for a ground vehicle is disclosed and includes obtaining an initial set of images with a camera on-board a vehicle, identifying features within the initial set of images, determining a three-dimensional pose using the visual features in the initial set of images, obtaining information indicative of vehicle movement with an inertial measurement unit, obtaining information indicative of vehicle movement with wheel speed sensors and a steering wheel angle sensor, fusing the identified features within the images, the vehicle movement from the IMU, and vehicle sensors within a two-dimensional plane, and determining a vehicle position relative to an initial start location based on the visual features in the images and the vehicle movement information from the IMU, wheel speed sensors, and the steering wheel angle.

Abstract: An automated vehicle parking system for a motor vehicle is disclosed and includes at least one camera obtaining images proximate a vehicle, at least one sensor array detecting objects proximate the vehicle, and a controller configured to generate a mask of an area proximate the vehicle from the images obtained by the at least one camera including labeled features identified within the obtained images and project the generated mask onto an occupancy grid generated with information from the at least one sensor array, wherein the controller is configured to locate a parking space responsive to open spaces defined within the generated mask.